# Creating value weighted portfolio returns. How to handle missing data?

I am creating portfolios using stock data.

I have some missing data for certain months.

What is the best way to handle this? Should I treat missing months as a return of zero?

I want to try and replicate Kenneth Frenches data, so if anyone had any insight into how that it dealt with in creating his portfolios would be useful.

To give an example,

WSay I've got two stocks, A and B, both starting with a weight of 50%, in month 1, the return of A is 10% and the Return of B is -10%, in the next month the weights 55% and 45% for A and B respectively, however, the return of A is 10% and the return of B is missing. So in month two will, I display the return of my portfolio as 10% or 5.5%, or something else?

Fama and French (1992) state that they "calculate each portfolio's monthly equal-weighted return for July of year $$t$$ to June of year $$t+1$$" (see, e.g. Table IV). In that case, it would appear that the results should be fairly insensitive to missing returns, since one would just calculate the average of all of the non-missing stocks.